Linear optimization: Parametrical objective function 4: Unterschied zwischen den Versionen
[unmarkierte Version] | [unmarkierte Version] |
Ailli (Diskussion | Beiträge) (→Basic Knowledge) |
Ailli (Diskussion | Beiträge) (→Basic Knowledge) |
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Zeile 8: | Zeile 8: | ||
− | To include large changes in the input data you have to add a new variable "q". For simple cases you just summate the new variable "q" multiplicated with a constant vektor " | + | To include large changes in the input data you have to add a new variable "<math>q</math>". For simple cases you just summate the new variable "<math>q</math>" multiplicated with a constant vektor " <math>\beta</math> " to the objective function. In this case the constant vektor is the value which change the input parameter "<math>c</math>". |
The objectiv function is now with a parameter: | The objectiv function is now with a parameter: |
Version vom 26. Juni 2013, 15:26 Uhr
Parametrical objective function is a special part of linear optimization. The foundation of parametrical optimization is the sensitivity analysis. Compared to the sensitivity analysis the Parametrical objective function makes a statement about large changes in the input data.
Basic Knowledge
To include large changes in the input data you have to add a new variable "". For simple cases you just summate the new variable "" multiplicated with a constant vektor " " to the objective function. In this case the constant vektor is the value which change the input parameter "".
The objectiv function is now with a parameter:
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): c(q)=c+q*
Thereby there is a new optimization problem which can be solved.
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \rightarrow
Fehler beim Parsen (http://mathoid.testme.wmflabs.org Serverantwort ist ungültiges JSON.): \ge